Using LabVIEW to Acquire and Analyze Motor Vibrations

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"Due to the sophistication of LabVIEW, we expanded the capabilities of our vibration monitoring system. Using the NI Sound and Vibration Measurement Suite, we could also take rotational speed and motor flux into account."

- Aravind Vaithilingam Chockalingam, UCSI University

The Challenge:
Developing an online machine condition monitoring system that can acquire and analyze motor vibrations, analyze the results in real time, and detect any problems before the machinery fails.

The Solution:
Using the NI USB-6008 data acquisition (DAQ) device, NI LabVIEW system design software, and the NI Sound and Vibration Suite to build a system that compares the vibration of a faulty motor with the vibration of a motor in good condition.

Aravind Vaithilingam Chockalingam - UCSI University
Chan Wei Yip - UCSI University
Raiparthiban Kumar - UCSI University


Predictive and preventive maintenance requires some means of assessing the actual condition of the machinery, and we can often detect early failure using condition monitoring techniques. We needed to build a continuous machine condition monitoring system to capture real-time data from equipment under test, such as rotating and reciprocating machinery. By comparing actual and desired performance behavior, we can predict and identify problems before they actually cause the equipment to stop working, thereby reducing the overall number of failures.

Although machine condition monitoring traditionally relies on vibration measurements, the performance of preventive machine condition monitoring can integrate other process parameters using deterministic and stochastic measurement analysis. Vibration is the harmonic, periodic, and random motion of a rotating machine. To monitor vibration, we use a sensor that separates the frequencies and quantifies the amplitude. Because vibration frequency and amplitude cannot be measured by sight or touch, the instrument helps convert the vibration into a usable quantity that can be processed and displayed along a frequency axis. The sensor output shows how fast the machine is moving (frequency) and how much the machine is moving (amplitude). Vibrational frequency indicates the problem with the machine, and the amplitude  indicates the relative severity of the problem. Certain frequencies only occur in the presence of conditions that indicate an impending defect. By comparing the vibration spectra of new equipment with the spectra of faulty equipment, we can determine when to intervene for maintenance. Misalignment and looseness commonly generate vibrations in operating machines, and even a small amount of imbalance can cause high distortion in the signal.

Due to the sophistication of LabVIEW, we expanded the capabilities of our system. In addition to vibration monitoring, we took rotational speed and motor flux into account. We used the NI Sound and Vibration Measurement Suite to divide the frequency spectrum into bands correlated with established potential failure causes. For instance, rotor imbalance often produces a recognizable vibration signal with a frequency that is one times the turning speed of the machine, and offset misalignment often produces a vibration signal with a frequency that is two times the turning speed of the machine. We used a fan motor as the benchmark for vibration analysis because it can generate blade pass frequency, which is the number of blades times the speed.

The experimental procedure consists of three segments, namely the test bench setup, the sensing setup, and the data handling setup. Figure 1 shows a representation of our simple block diagram. The test bench includes a reference motor in good condition, a faulty motor with the same specifications, and an NI USB-6008 as the hardware interface to the system.  The sensing setup includes an accelerometer to measure vibration, optical encoders to measure speed, and a National Semiconductor LM35 to measure temperature.

Data Acquisition, Analysis, and Presentation

We used NI USB DAQ to communicate the sensor measurements into the LabVIEW environment. We also used the low-cost multifunction NI USB-6008 DAQ device to acquire and capture the test data to disk for analysis. The USB-6008 uses the NI-DAQmx driver software and works with LabVIEW. In addition, we developed a programming interface for data acquisition, which uses the Sound and Vibration Measurement Suite to analyze the data and determine which part of the equipment under test failed. The hardware setup, which acquires the  current and voltage data, connects with a PC running Windows OS via the USB hub and the NI-DAQmx driver software.

We also developed a GUI so users can understand and evaluate the entire system under test. Motor A represents a reference motor in good condition and Motor B represents a similar motor in bad condition. Figure 5 shows the vibration results for a short test and a longer test, respectively.

Author Information:
Aravind Vaithilingam Chockalingam
UCSI University
1 Jalan Menara Gading, Cheras
Tel: +603 91018880
Fax: +60391023606

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